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Recent advances in development and application of assays/algotithms for detection of recent HIV infections and estimation of incidence Michael Busch, MD, PhD Blood Systems Research Institute University of California San Francisco CDC/APHL HIV Diagnostics Conference, 2010

Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

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Page 1: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Recent advances in development and application of assays/algotithms for

detection of recent HIV infections and estimation of incidence

Michael Busch, MD, PhDBlood Systems Research Institute

University of California San Francisco

CDC/APHL HIV Diagnostics Conference, 2010

Page 2: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Why its important to detect pre-SC window-phase HIV infections?

• Prevent viral transmission by blood transfusions and organ and tissue transplants

• Identify early infections in public health screening and diagnostic settings – acute-viremic phase of infection is highly

infectious– more effective response to treatment if initiated

during acute compared to chronic stages? – prevent secondary transmission by contact tracing

and counseling to modify risk behaviors• Identify subjects in primary infection for

pathogenesis, treatment and vaccine research

Page 3: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

HIV acute and early infection

HIV RNA (plasma)HIV Antibody

11

0 10 20 30 40 50 60 70 80 90 100

HIV p24 Ag

16 22

Ramp-up viremiaDT = 21.5 hrs

1st gen2nd gen

3rd gen

p24 Ag EIA -

HIV MP-NAT -

HIV ID-NAT -

Peak viremia: 106-108 gEq/mL

Viral set-point: 102 -105 gEq/mL

Closing the infectious window period

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HIV-1 transmission by transfusion of blood from SC donors according to the interdonation interval

Interdonation interval (days) Total

HIV-1 transmission

Number Percentage

45 - 90 17 13 76

91 - 180 29 8 28

181 - 360 48 9 19

361 - 540 39 5 13

541 - 720 14 0 0

> 720 32 1 3

Total 179 36 20

Peteresen et al. Transf. 1994 34 : 283-9Interdonation interval (days)

Prob

abilit

y of

tra

nsm

issi

on

0.0

0.2

0.4

0.8

1.0

0.6

2000 500400300100

56 day infectious WP (42 days w/ EIA 2.0)

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HIV Stage Progression based on 51 Seroconverting Plasma Donors

Fiebig et al. AIDS, 17:1871-9, 2003Lee et al. J Theor Biol, 2009

Page 6: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

The Incidence Rate / Window Period (WP) Model Allows Prediction of Test Yields for Direct HIV

Assays (p24 Ag, HIV RNA) vs. EIA Antibody Test

Test Yield (per unit) =

Incidence Rate (person-years) x Decrease in WP (fraction of year)

Page 7: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Projected WP Closure and Yield of p24 Ag, MP and ID NAT Assays Relative to a Sensitive HIV-1/2 EIA Antibody Test in the Detection of WP HIV Infection

Assay Sensitivity

[gEq / mL]

WP Closure

[days]

Yield, WP HIV Infections per 1,000 Persons Tested in Various Screening Settings

[ Representative Incidence Rate / Person-Years ]

Blood Donors[ 2 / 100,000 = 0.002% ]

STD Clinic[ 1 / 1,000 = 0.1% ]

High Risk Clinic[ 1 / 10 = 10% ]

p24 Ag 10,000 6 0.00033 0.016 1.6

MP NAT 1,000 9 0.00049 0.025 2.5

ID NAT 50 13 0.00071 0.036 3.6

Fiebig et al. AIDS, 17:1871-9, 2003

Page 8: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

102 acutely infected plasma donor panels

3476 complete env sequences from single genome amplifications

Inferred consensus sequence at estimated time of virus transmission

78 donors infected by single virion; 24 by 2-5 virions

Page 9: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Why Determine HIV Incidence?• Characterize the epidemic in a population

– Monitor changes over time– Identify important sub-populations for interventions

• Assess impact of programs• Identify populations for HIV intervention trials

– Endpoint of intervention trials• Identify individuals for interventions

– Prioritization– Interrupt transmission

Page 10: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Standard Methods for Incidence Determination are Unsatisfactory

• Indirect methods; repeat cross-sectional measurements; modeling

• Prospective follow-up is expensive and unrepresentative

• Enrollment in cohorts leads to behavior change• Back calculation methods not timely or

reliable

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HIV Incidence Using Early Diagnostic Tests

RNA+ Ab-P24+ Ab -

RNA

p24

Ab

seroconversion

days

Res

pons

e

infection

Detection limit

Brookmeyer, Quinn.Am J Epi 1995

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Page 13: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

July 1998

Abbott EIA 3A11 assay: sensitive/less-sensitive(“detuned”)

Page 14: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Recent Infection Testing Algorithm (RITA)

RITA duration

RNA

p24

Ab

seroconversion

Antibody cutoff:Quantity (LS-EIA)Proportion (BED)AvidityIsotypeSpecificity of Ag

days

Res

pons

e

infection

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Cross-Sectional Incidence Formula

AnnualizedIncidence =

(# who test recent) X (365/window period)

# at riskX 100

I =(365/w) Nrecent

Nseronegative + ½ (365/w) Nrecent

X 100

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Survey size = 1000

HIV-seropositive = 100 (10%)

Recent on incidence assay = 10

RITA duration = 170 days

2.15 x 10Incidence = x 100 = 2.33% per year

900 + 21.5

HIV Incidence and RITA:Cross-Sectional Surveys

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The Ideal Assay for Recent Infection• Describes a distinct “detection window” of relatively

uniform duration• Is universally positive in recent infection and negative

later in infection (or vice versa)• Is unaffected by:

– virus subtype– mode of transmission– therapy– OI and AIDS– Age, sex, race

• Has a relatively long window, all else being equal

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0

0.5

1

1.5

2

2.5

3

3.5

0 200 400 600 800 1000 1200

RITA and Misclassification

Days

SOD

Mean

Mis-Classified

Long-standing

Misclassified Recent

170 days

Cutoff

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-BED competitive capture EIA-Indirectly measures HIV-IgG as a proportionof total IgG

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Amsterdam Cohort/ subtype B

0

0.5

1

1.5

2

2.5

3

3.5

4

0 200 400 600 800 1000

Days Since Seroconversion

OD

-n

127 days

Zimbabwe Seroconverters/C

0

1

2

3

4

0 200 400 600 800 1000

Days since SC

OD

-n

ENARP Serovonverters/C

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 200 400 600 800 1000

Days since SC

OD

-n

Kenya, A and D

0

0.5

1

1.5

2

2.5

3

3.5

4

0 200 400 600 800 1000

Days Since Seroconversion

OD

-n

181 days

167 days 171 days

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Distribution of Window Periods for BED

from 768 seroconverters

-1

0

1

2

3

4

5

6

7

0 20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

320

340

360

380

400

420

440

460

480

510

530

550

580

700

BED Window Period (Days)

Perc

enta

ge

Observed Estimates

Mean ω=197 days

5.9% > 2x mean ω to reach cutoff

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Challenges to Using Antibody Maturation to Identify Recent Infection

• Variable immune response among individuals– Antibody response related to viral level

• Variability by HIV-1 subtypes• False-recent status (long-term specificity)

– Elite controllers (low viral levels)• Accumulate in population

– ART use (low viral levels)– Advanced HIV disease (AIDS)

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2008

Proposed determination and use of a factor epsilon ( ε ) to correct for misclassification of long-standing infections as recent.

Page 24: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

HIV Incidence Assays• “Detuned” assays

– Abbott 3A11 - unavailable– bioMérieux Vironostika HIV-1 – Avioq– Ortho Vitros ECi

• BED-Capture EIA (Calypte; Trinity)

• Avidity assays– Run on Abbott AxSYM– Bio-Rad – Run on Ortho Vitros analyzer

• IDE-V3 assay• IgG3 anti-HIV• Inno-LIA HIV adaptation

Page 25: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic
Page 26: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

September 2008

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What Needs to be Done• WHO Technical WG on HIV Incidence Assays

– www.who.int/diagnostics_laboratory/links/hiv_incidence_assay

• Guidance on assay use• Solidify consensus on mathematical issues• Define the assay development pathway• Define and assemble specimens for assays

calibration and validation• Engage industry on assay development

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Assay Calibration and Validation• Establish “RITA Interval” and “False Recent Rate”• Requires large numbers of well-characterized

seroconversion panels and FRR panels– Various populations and sub-populations

• Geographic, transmission modes, etc.

– Various HIV-1 subtypes– Early and long-standing infections– Co-infections (TB, malaria)

• Such specimens aren’t readily available in sufficient volume in a central location

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WHO HIV Technical Working Group on HIV Incidence

Guidance DocumentWhen and how to use assays for recent infection to estimate HIV incidence at a population level

Prepared on behalf of the World Health Organization Technical Working Group on HIV Incidence Assays With support of a grant from the Bill & Melinda Gates Foundation

Page 30: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Steps involved in applying RITA to estimate HIV incidence

Step 1: Identify study population

• The study population for which incidence will be calculated should be clearly defined.• The sampling frame that provides the subset for incidence testing should also be well defined.• Refer to Chapter 4 for guidance on this step.

Step 2: Identify HIV positive individuals

• Identify HIV positive individuals by testing the study population or the sampled subgroup for anti-HIV antibody or HIV RNA or DNA.

• Choice of tests and testing strategy should be based on local guidelines and consistent with WHO guidelines for HIV testing.

Step 3: Apply the Recent Infection Testing Algorithm (RITA)

• The RITA is applied to specimens of HIV infected individuals. The RITAs which may be utilised are:• RITA based on a single assay for recent infection • RITA based on a laboratory assay for recent infection combined with other clinical information

• Mean RITA duration must be known and false recent rate (FRR) must be calculated.• Refer to Chapter 6 for guidance on choice of RITA and the Appendix for the calculation of FRR.

Step 4: Analysis of resulting data

• HIV incidence is calculated using the counts from the RITA, the FRR and mean RITA duration.• Refer to Chapter 7 for guidance on estimating HIV incidence.

Page 31: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Application of a RITA based on a laboratory assay for recent infection and additional clinical information

HIV infected individuals

Assay for recent

infection*

Recent infection

Non-recent infection

Sample from recently HIV infected subject

CD4 count

Negative for AIDS illness

CD4 <200 cells/mm3

Negative

Non-recent infection

* Known mean RITA duration

Non-recent infection

PositiveNon recent infection

Anti-retroviral

testing

CD4 ≥200 cells/mm3

AIDS illness

Diagnosis of AIDS illness

Non-recent infection

History of HIV

infection

HIV diagnosis <1 year prior

Non-recent infection

Diagnosis ≤1 year prior or no previous HIV diagnosis

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Performance in Clade B of BED + Avidity Testing Algorithm

Estimated Window Period using HIVNET & Vaxgen004 (154 subjects , median 4 samples / subject)

Avidity & BED cutoff Values

Mean Recency Period

(95% Conf Limits)

30% , 0.6 117.3 (93.1, 141.4)

40%, 0.8 143.0 (117.8, 168.2)

40%, 1.0 163.6 (138.0, 189.1)

50%, 0.8 147.8 (122.0, 173.5)

80%, 1.0 203.8 (170.0, 237.6)

Misclassification Rate in Known Chronically Infected Individuals (2 to 8 yrs post infection)Avidity & BED cutoff Values

MACS N= 341 individuals

ALIVEN= 284 individuals

30% , 0.6 0.58% (2/341)

0.35% (1/284)

40%, 0.8 0.74% (3/341)

0.35% (1/284)

40%, 1.0 0.74% (3/341)

0.35% (1/284)

50%, 0.8 2.35% (8/341)

0.35% (1/284)

80%, 1.0 3.81% (13/341)

3.52% (10/284)

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Incidence Comparison at Johns Hopkins Emergency Department 2001 & 2007

Clade B epidemicUse BED 0.8 & Avidity 40%Assume 143 day window periodMisclassification rate of 0.7%

Survey year2001 2007

HIV negative 1366 4154HIV positive 183 321Recent positives 8 4

Incidence Estimates 1.26% 0.11%

One sided P value for difference = 0.0008

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X

Page 35: Recent advances in development and application of assays ... · Recent advances in development and application of assays/algotithms for ... screening and diagnostic settings – acute-viremic

Acknowlegements• Oliver Laeyendecker• Sue Eshleman• Bharat Parekh• Bernie Branson• Andrea Kim• Connie Sexton• Mary Lynn Baniecki• Karine Dube• Megan Averill• Renee Ridzon• Bill Rodriguez• Christine Rousseau

• Tim Mastro• Chris Pilcher• John Kaldor• Txema Garcia-Calleja• Gaby Vercauteren• Thomas Rehle• Alex Welte• Tom McWalter• Tim Hallett• Michelle Owen• Joanne Micallef• Gary Murphy